System and method for displaying images utilizing multi-blending

• US 20050093890A1
• Filed: 06/03/2004
• Published: 05/05/2005
• Est. Priority Date: 06/12/2003
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Baudisch, Patrick M.
• Granted Patent: US 7,667,717 B2
• Time in Patent Office: Days
• US Class Current: 345/639
• CPC Class Codes: G06T 15/503 Blending, e.g. for anti-aliasing
• CPC Class Codes: G09G 2340/10 Mixing of images, i.e. displayed pixel being the result of an operation, e.g. adding, on the corresponding input pixels
• CPC Class Codes: G09G 2340/14 Solving problems related to the presentation of information to be displayed
• CPC Class Codes: G09G 5/026 Control of mixing and/or overlay of colours in general G09G5/022 and G09G5/024 take precedence
• CPC Class Codes: G09G 5/14 Display of multiple viewports

Abstract

A system and method for processing images utilizing varied feature class weights is provided. A computer system associates two or more images with a set of feature class data, such as color and texture data. The computer system assigns a set of processing weights for each of the feature classes. The two or more images are blended according to the feature class weights. The blended image can be further adjusted according to the content of the images.

Claims

1. A method for processing two or more images represented by a set of feature classes, the method comprising:

associating each of the two or more images with a set of feature class data;

assigning a processing weight for each feature class; and

processing the set of feature class data according to the assigned processing weight to generate a blended image.

2. The method as recited in claim 1, wherein the set of feature class data corresponds to color class data.

3. The method as recited in claim 2, wherein the color class data corresponds to CIE Lab color model data.

4. The method as recited in claim 1, wherein the set of feature class data corresponds to texture class data.

5. The method as recited in claims 4, wherein the texture class data corresponds to edge data.

6. The method as recited in claim 1, wherein the processing weight for each feature class is specified as a range of numbers between zero and one.

7. The method as recited in claim 1, wherein the processing weight for each feature class is specified as a Boolean value.

8. A computer-readable medium having computer-executable instructions for performing the method recited in claim 1.

9. A computer system for performing the method recited in claim 1.

10. A method for blending a foreground image and a background image, wherein the foreground and background images are represented by a set of feature classes, the method comprising:

assigning a processing weight for each feature class;

processing the set of feature class data for the foreground and background image according to the assigned processing weight to generate a blended image; and

adjusting the blended image according to the content of the foreground and background image.

11. The method as recited in claim 10, wherein the set of feature class data corresponds to color class data.

12. The method as recited in claim 11, wherein the color class data corresponds to CIE Lab color model data.

13. The method as recited in claim 10, wherein the set of feature class data corresponds to texture class data.

14. The method as recited in claim 10, wherein the processing weight for each feature class is specified as a range of numbers between zero and one.

15. The method as recited in claim 10, wherein the processing weight for each feature class is specified as a Boolean value.

16. The method as recited in claim 10, wherein adjusting the blended image includes blurring the background image.

17. The method as recited in claim 10, wherein adjusting the blended image includes;

obtaining usage data for at least a portion of the foreground image; and

adjusting the image according to the usage data.

18. The method as recited in claim 17, wherein adjusting the image includes diminishing the opacity of portions of the foreground imaged based on the usage data.

19. The method as recited in claim 10, wherein adjusting the image includes mapping values from a first feature class of the foreground image to another feature class.

20. A computer-readable medium having computer-executable instructions for performing the method recited in claim 10.

21. A computer system for performing the method recited in claim 10.

22. A method for processing two or more images represented by a set of feature classes, the method comprising:

associating each of the two or more images with a set of feature class data;

assigning a processing weight for each feature class;

processing the set of feature class data according to the assigned processing weight to generate a blended image; and

adjusting the blended image according to the content of the two or more images.

23. The method as recited in claim 22, wherein the set of feature class data corresponds to color class data.

24. The method as recited in claim 23, wherein the color class data corresponds to CIE Lab color model data.

25. The method as recited in claim 22, wherein the processing weight for each feature class is specified as a range of numbers between zero and one.

26. The method as recited in claim 22, wherein the processing weight for each feature class is specified as a Boolean value.

27. The method as recited in claim 22, wherein adjusting the blended image includes blurring at least one of the two or more images.

28. The method as recited in claim 22, wherein adjusting the blended image includes;

obtaining usage data for at least a portion of one of the two or more images; and

adjusting the image according to the usage data.

29. The method as recited in claim 28, wherein adjusting the image includes diminishing the opacity of portions of the one of the two or more images based on the usage data.

30. The method as recited in claim 22, wherein adjusting the image includes mapping values from a first feature class of the foreground image to another feature class.

31. A computer-readable medium having computer-executable instructions for performing the method recited in claim 22.

32. A computer system for performing the method recited in claim 22.